About Peak3

Peak3 is an award-winning vertical SaaS provider, enabling more relevant, convenient, and affordable insurance protection for everyone through our technology and ingenuity. Together with our clients, we create a more resilient and innovative future.

We combine insurance core, distribution, and AI solutions to deliver a step change in performance for insurers, MGAs, and insurance intermediaries. From greenfield embedded insurance ventures to multi-country core modernization programs, our SaaS solutions power top customers across life, health, and P&C; insurance.

Our 500+ colleagues are based across over 15 countries in Europe, Asia and the Middle East – with an ambitious roadmap to scale further.

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About the Role

As an AI Platform Engineer on the AI Platform team, you'll build and operate the infrastructure that keeps our agentic AI systems fast, reliable, and cost-effective in production. Working closely with our Principal AI Full-Stack Engineer, you'll take architectural direction and turn it into solid, well-monitored infrastructure — vector databases, model gateways, inference pipelines — that the rest of the team builds on.

Responsibilities

- Build and maintain core AI infrastructure: vector databases, semantic retrieval, model gateways, and inference pipelines.
- Implement inference optimization and caching to keep latency and cost within target.
- Set up and maintain observability for LLM systems — logging, tracing, evals monitoring, cost tracking.




- Support production incidents and on-call for AI systems, including runbooks and postmortems.
- Work with the Principal AI Full-Stack Engineer to implement architecture decisions and contribute to full-stack features when needed.

Experience & Qualifications

- Solid experience in Python or TypeScript, with working knowledge of backend infrastructure and cloud-native deployment (K8s or serverless).
- Hands-on experience with vector databases, embedding models, and model deployment/serving patterns.
- Some experience with LLM inference optimization, caching, and observability tooling.
- Familiarity with RAG pipelines, function/tool calling, or agent frameworks (LangGraph, LlamaIndex, or similar) — deep expertise not required, willingness to grow into it is.
- Comfortable operating in production environments and taking ownership of reliability and performance.
- High agency and a builder mindset — willing to dig into infra problems without waiting for complete specs.

Nice to Have

- Experience with secure code execution sandboxes (gVisor, Firecracker, WASM) or long-running workflow orchestration.
- Exposure to model routing across providers or agent memory/state architectures.
- Interest in distributed systems, cost governance, or FinOps for AI workloads.
- Finance or insurance domain experience (not required — engineering fundamentals and learning velocity matter more).

Our stack: Python, TypeScript, React/Next.Js, Postgres, Kubernetes, and various vector databases and LLM providers. xhfqzwm Prior experience with every part isn't required — strong fundamentals and fast learning matter more.

📌 Ai Platform Engineer - Madrid
🏢 Jobrapido
📍 Madrid